Glintbase

# Glintbase MCP Server (ARS 3.0) **Glintbase** is the open audit and simulation standard for the autonomous AI agent web. It gives AI coding agents (Claude Code, Cursor, Windsurf, Devin, Antigravity) empirical visibility into whether a website, developer portal, or API is truly agent-ready—or full of silent friction, 404 traps, and schema hallucinations. Built on the **Agent Readiness Score (ARS 3.0)** specification, this MCP server provides instant surface discovery, lightweight scorecards, flight simulation with visual SVG telemetry, and 9 bundled remediation playbooks. --- ## ✨ Features - **Empirical ARS 3.0 Scoring**: Evaluates domains across 6 core pillars: *Discovery*, *Access*, *Usability*, *Semantic*, *Architecture*, and *Safety*. - **Machine Surface Discovery**: Automatically detects and validates `robots.txt` AI policies, `/llms.txt`, `/llms-full.txt`, `/.well-known/ard.json`, `/auth.md`, and OpenAPI specifications. - **Visual Flight Simulator**: Simulates synthetic coding personas (Claude Code, Cursor, Perplexity) executing developer journeys, outputting visual SVG journey trees, schema friction metrics, and token-tax telemetry. - **Context-Preserving Scores**: Fetch ultra-compact scorecards in under 200 tokens to preserve agent context windows during automated workflows. - **9 Bundled Playbooks**: Instant access to complete ARS 3.0 remediation manuals (living artifacts, WorkOS auth contracts, streamable MCP servers, and CI gates). --- ## 🛠️ Tools | Tool | Parameters | Description | | :--- | :--- | :--- | | `glintbase_audit` | `target` (string) | Runs a complete 119-check ARS 3.0 audit on any target URL. Returns detailed layer breakdowns, passed/failed checks, and actionable remediation diffs. | | `glintbase_get_score` | `target` (string) | Returns an ultra-compact score card (<200 tokens) with letter grade, archetype classification, and layer scores. Ideal for rapid CI checks. | | `glintbase_discover_surfaces` | `target` (string) | Scans and maps all machine entrypoints (`robots.txt`, `llms.txt`, `ard.json`, `auth.md`, OpenAPI, sitemap). | | `glintbase_simulate_flight` | `target` (string), `persona` (enum: `claude-code`, `cursor`, `perplexity`), `intent` (string) | Runs an autonomous mission simulation. Returns step-by-step navigation telemetry, token consumption, and a visual SVG journey tree graphic. | | `glintbase_get_skill` | `skillName` (string) | Retrieves full, multi-step ARS 3.0 remediation playbooks (e.g. `agent-readiness`, `living-artifacts`, `agent-auth`, `mcp-hardening`). | *Note: All tools support both `glintbase_*` names and canonical short names (`audit`, `get_score`, `discover_surfaces`, `simulate_flight`, `get_skill`).* --- ## 📚 Bundled Prompts & Resources ### Prompts - `optimize_agent-readiness`: Master workflow for elevating a codebase to ARS 3.0 standards. - `optimize_living-artifacts-architect`: Step-by-step guidance for authoring `llms.txt`, `llms-full.txt`, and `ard.json`. - `optimize_agent-auth-handbook`: Blueprint for RFC 9728 machine-to-machine authentication contracts (`auth.md`). - `optimize_streamable-mcp-builder`: Architectural guide for deploying streamable HTTP MCP servers. - `optimize_flight-simulator-replay`: Diagnostic playbook for analyzing agent bottlenecks. ### Resources - `skill://glintbase/agent-readiness`: Master ARS 3.0 Playbook. - `skill://glintbase/living-artifacts`: Living Artifacts Specification. - `skill://glintbase/agent-auth`: Agent Authentication Handbook. - `glintbase://schemas/ars3-spec`: Complete ARS 3.0 evaluation schema. - `glintbase://standards/auth-contract`: RFC 9728 machine auth template. --- ## 🚀 Quick Start ### Option A: Smithery CLI ```bash npx -y @smithery/cli install @glintbase/mcp --client claude

Readiness is how fully this listing follows its protocol and how it behaved in our probes over 30 days. It is shown for reference and does not move it in search. Search order and leaderboards use the separate quality grade (here C+, 66.0/100), which weighs availability, conformance, p95 speed and descriptor. How the two differ

Compared with peers

Against 53,039 reachable MCP servers in our daily snapshot (2026-11-12 06:46 UTC). Display only; it does not change search order.

Readiness

Higher than 80% of peers

This listing 86 · peer median 81

Latency

Faster than 5% of peers

This listing 1,688 ms · peer median 326 ms

How many agent tools actually work · All statistics

Listed in

Directories this entry was found in.

How to connect

https://glintbase.dev/api/mcp

curl -X POST https://glintbase.dev/api/mcp \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json, text/event-stream' \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{}}'